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      Natural history bycatch: a pipeline for identifying metagenomic sequences in RADseq data

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      PeerJ
      PeerJ Inc.
      Metagenomics, DNA barcoding, Parasitology, Museum resources

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          Abstract

          Background

          Reduced representation genomic datasets are increasingly becoming available from a variety of organisms. These datasets do not target specific genes, and so may contain sequences from parasites and other organisms present in the target tissue sample. In this paper, we demonstrate that (1) RADseq datasets can be used for exploratory analysis of tissue-specific metagenomes, and (2) tissue collections house complete metagenomic communities, which can be investigated and quantified by a variety of techniques.

          Methods

          We present an exploratory method for mining metagenomic “bycatch” sequences from a range of host tissue types. We use a combination of the pyRAD assembly pipeline, NCBI’s blastn software, and custom R scripts to isolate metagenomic sequences from RADseq type datasets.

          Results

          When we focus on sequences that align with existing references in NCBI’s GenBank, we find that between three and five percent of identifiable double-digest restriction site associated DNA (ddRAD) sequences from host tissue samples are from phyla to contain known blood parasites. In addition to tissue samples, we examine ddRAD sequences from metagenomic DNA extracted snake and lizard hind-gut samples. We find that the sequences recovered from these samples match with expected bacterial and eukaryotic gut microbiome phyla.

          Discussion

          Our results suggest that (1) museum tissue banks originally collected for host DNA archiving are also preserving valuable parasite and microbiome communities, (2) that publicly available RADseq datasets may include metagenomic sequences that could be explored, and (3) that restriction site approaches are a useful exploratory technique to identify microbiome lineages that could be missed by primer-based approaches.

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          Most cited references32

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          BLAST+: architecture and applications

          Background Sequence similarity searching is a very important bioinformatics task. While Basic Local Alignment Search Tool (BLAST) outperforms exact methods through its use of heuristics, the speed of the current BLAST software is suboptimal for very long queries or database sequences. There are also some shortcomings in the user-interface of the current command-line applications. Results We describe features and improvements of rewritten BLAST software and introduce new command-line applications. Long query sequences are broken into chunks for processing, in some cases leading to dramatically shorter run times. For long database sequences, it is possible to retrieve only the relevant parts of the sequence, reducing CPU time and memory usage for searches of short queries against databases of contigs or chromosomes. The program can now retrieve masking information for database sequences from the BLAST databases. A new modular software library can now access subject sequence data from arbitrary data sources. We introduce several new features, including strategy files that allow a user to save and reuse their favorite set of options. The strategy files can be uploaded to and downloaded from the NCBI BLAST web site. Conclusion The new BLAST command-line applications, compared to the current BLAST tools, demonstrate substantial speed improvements for long queries as well as chromosome length database sequences. We have also improved the user interface of the command-line applications.
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            ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis

            Using non-conventional markers, DNA metabarcoding allows biodiversity assessment from complex substrates. In this article, we present ecoPrimers, a software for identifying new barcode markers and their associated PCR primers. ecoPrimers scans whole genomes to find such markers without a priori knowledge. ecoPrimers optimizes two quality indices measuring taxonomical range and discrimination to select the most efficient markers from a set of reference sequences, according to specific experimental constraints such as marker length or specifically targeted taxa. The key step of the algorithm is the identification of conserved regions among reference sequences for anchoring primers. We propose an efficient algorithm based on data mining, that allows the analysis of huge sets of sequences. We evaluate the efficiency of ecoPrimers by running it on three different sequence sets: mitochondrial, chloroplast and bacterial genomes. Identified barcode markers correspond either to barcode regions already in use for plants or animals, or to new potential barcodes. Results from empirical experiments carried out on a promising new barcode for analyzing vertebrate diversity fully agree with expectations based on bioinformatics analysis. These tests demonstrate the efficiency of ecoPrimers for inferring new barcodes fitting with diverse experimental contexts. ecoPrimers is available as an open source project at: http://www.grenoble.prabi.fr/trac/ecoPrimers.
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              Primer and platform effects on 16S rRNA tag sequencing

              Sequencing of 16S rRNA gene tags is a popular method for profiling and comparing microbial communities. The protocols and methods used, however, vary considerably with regard to amplification primers, sequencing primers, sequencing technologies; as well as quality filtering and clustering. How results are affected by these choices, and whether data produced with different protocols can be meaningfully compared, is often unknown. Here we compare results obtained using three different amplification primer sets (targeting V4, V6–V8, and V7–V8) and two sequencing technologies (454 pyrosequencing and Illumina MiSeq) using DNA from a mock community containing a known number of species as well as complex environmental samples whose PCR-independent profiles were estimated using shotgun sequencing. We find that paired-end MiSeq reads produce higher quality data and enabled the use of more aggressive quality control parameters over 454, resulting in a higher retention rate of high quality reads for downstream data analysis. While primer choice considerably influences quantitative abundance estimations, sequencing platform has relatively minor effects when matched primers are used. Beta diversity metrics are surprisingly robust to both primer and sequencing platform biases.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                16 April 2018
                2018
                : 6
                : e4662
                Affiliations
                Department of Ecology and Evolutionary Biology, University of Michigan Museum of Zoology, University of Michigan , Ann Arbor, MI, USA
                Author information
                http://orcid.org/0000-0001-6150-6150
                Article
                4662
                10.7717/peerj.4662
                5907781
                29682427
                50403c3b-cb4f-4002-869e-fcd45c638eb1
                © 2018 Holmes and Davis Rabosky

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 15 November 2017
                : 3 April 2018
                Funding
                Funded by: University of Michigan
                Funded by: University of Michigan Department of Ecology and Evolutionary Biology
                Funded by: University of Michigan Museum of Zoology
                Funding was provided by a startup grant from the University of Michigan to Alison R. Davis Rabosky and University of Michigan Department of Ecology and Evolutionary Biology and University of Michigan Museum of Zoology graduate student grants to Iris Holmes. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biodiversity
                Ecology
                Evolutionary Studies
                Genomics
                Parasitology

                metagenomics,dna barcoding,parasitology,museum resources

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